
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "71"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 120 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 115 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	RF_maintenance	100.00%	12.97%	100.00%	0.00%	100.00%	0.00%	1.378939	11.722821	0.372146	81.897449	16.515160	27.272175	9.815520	30.873551	0.5563	0.0776	0.2608	7.552645	1.229848
2459593	RF_maintenance	100.00%	51.38%	100.00%	0.00%	100.00%	0.00%	7.336283	19.146878	0.662524	86.572841	11.624808	37.867260	6.693688	11.573720	0.4827	0.0682	0.2337	4.584119	1.218828
2459592	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	-0.287071	1.378692	-0.672283	8.015771	0.433089	1.491677	1.687949	0.310718	0.0354	0.0330	0.0072	nan	nan
2459591	RF_maintenance	100.00%	91.35%	100.00%	0.00%	100.00%	0.00%	39.312773	21.760810	7.852676	100.623600	12.201321	32.479000	4.965328	2.170666	0.3188	0.0509	0.1265	9.969322	1.234200
2459590	RF_maintenance	100.00%	97.30%	100.00%	0.00%	100.00%	0.00%	26.497523	25.334703	3.690907	93.743379	15.173037	34.974526	5.010269	3.905712	0.3078	0.0574	0.0970	4.221945	1.245837
2459589	RF_maintenance	100.00%	56.73%	100.00%	0.00%	100.00%	0.00%	4.384154	23.049977	-0.200154	86.880233	7.051587	22.068016	5.449882	16.967532	0.4520	0.0751	0.1752	3.844819	1.215580
2459588	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	194.373067	223.882253	inf	inf	27.128322	26.913538	77.138415	17.974200	nan	nan	nan	0.000000	0.000000
2459587	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	9.793991	22.937823	3.228911	135.735987	-23.333991	-23.858603	-4.675000	-4.393628	nan	nan	nan	3.516702	1.146800
2459586	RF_maintenance	100.00%	77.84%	100.00%	0.00%	100.00%	0.00%	11.422477	20.523360	-0.162956	32.658232	9.704209	11.501380	0.959296	6.564874	0.3408	0.0566	0.1175	6.142557	1.246359
2459585	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.597424	25.451239	-1.167380	11.197068	-0.892083	10.169081	1.242195	4.741655	0.0452	0.0344	0.0042	0.000000	0.000000
2459584	RF_maintenance	100.00%	89.80%	100.00%	0.00%	100.00%	0.00%	53.636082	26.185032	8.660800	116.219287	13.207510	18.749041	27.147220	32.719770	0.3028	0.0435	0.0970	2.362369	0.954143
2459583	RF_maintenance	100.00%	89.14%	100.00%	0.00%	100.00%	0.00%	41.782555	19.473466	2.076171	36.043644	4.619789	23.447923	0.947878	0.219426	0.3368	0.0514	0.1226	9.351891	1.183092
2459582	RF_maintenance	100.00%	88.65%	100.00%	0.00%	100.00%	0.00%	35.767078	16.803595	1.759398	32.746671	7.558176	28.420366	0.781667	0.343983	0.3144	0.0437	0.1264	12.579096	1.179137
2459581	RF_maintenance	100.00%	88.65%	100.00%	0.00%	100.00%	0.00%	49.416481	23.309760	1.885354	36.946487	9.747974	22.951372	26.393737	0.364153	0.3345	0.0527	0.1020	5.238741	1.213385
2459580	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459579	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459578	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	-0.110069	1.724199	-0.505883	3.007688	0.549826	0.478090	2.639501	1.461547	0.0360	0.0365	0.0083	nan	nan
2459577	RF_maintenance	100.00%	95.24%	100.00%	0.00%	100.00%	0.00%	6.019343	22.619205	0.030350	34.555098	3.308030	24.862870	0.384119	0.375362	0.3148	0.0509	0.0731	2.885035	1.211779
2459576	RF_maintenance	100.00%	91.84%	100.00%	0.00%	100.00%	0.00%	0.725793	17.393104	0.050293	27.705956	2.727400	22.003993	0.839498	1.041000	0.3257	0.0544	0.0591	4.676141	1.268380
2459575	RF_maintenance	100.00%	45.92%	100.00%	0.00%	100.00%	0.00%	8.029280	18.456001	0.111547	27.519095	5.465696	17.054124	2.952602	6.040079	0.4350	0.0661	0.1659	3.488611	1.196501
2459574	RF_maintenance	100.00%	83.33%	100.00%	0.00%	100.00%	0.00%	1.632199	16.406255	-0.056595	26.329399	2.683900	24.311538	-0.093254	0.648443	0.3286	0.0500	0.0613	3.401470	1.205053
2459573	RF_maintenance	100.00%	84.91%	100.00%	0.00%	100.00%	0.00%	32.648589	16.893020	2.226252	45.291770	6.479513	28.288474	-0.405241	1.383965	0.3431	0.0485	0.0987	7.613669	0.824416
2459572	RF_maintenance	100.00%	94.05%	100.00%	0.00%	100.00%	0.00%	25.506483	17.012898	0.579620	26.487117	17.497801	17.989520	1.222141	2.501735	0.3277	0.0525	0.0818	11.085203	1.247497
2459571	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	0.165407	1.389781	-0.332559	3.091250	-0.752461	0.556586	-0.486902	1.403117	0.0367	0.0381	0.0080	nan	nan
2459570	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459569	RF_maintenance	100.00%	42.75%	53.46%	0.00%	100.00%	0.00%	4.366973	1.578930	-0.163116	3.058083	2.771978	95.955233	2.810030	13.753406	0.5530	0.4455	0.0981	6.037722	1.228782
2459566	RF_maintenance	100.00%	87.03%	0.00%	0.00%	100.00%	0.00%	17.206943	0.056080	0.557627	4.254126	17.572285	4.421214	4.450117	0.742316	0.3105	0.6298	0.2826	2.870283	3.049395
2459565	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	-1.185954	-1.185954	-1.077553	-1.077553	-0.891166	-0.891166	-0.958079	-0.958079	nan	nan	nan	0.000000	0.000000
2459564	RF_maintenance	100.00%	84.44%	0.00%	0.00%	100.00%	0.00%	11.645454	3.106000	0.679307	3.307221	1.832257	0.325131	1.579354	-1.210313	0.3460	0.6252	0.2462	4.914416	2.714442
2459563	RF_maintenance	100.00%	86.44%	0.00%	0.00%	100.00%	0.00%	15.159610	7.181805	19.160525	25.033079	12.961780	16.421702	1.639475	-1.465907	0.3264	0.6172	0.2537	6.224217	2.026718
2459562	RF_maintenance	100.00%	84.91%	0.00%	0.00%	100.00%	0.00%	11.205418	1.953474	-0.251907	1.224425	0.874428	0.258640	0.535294	-0.986483	0.3492	0.6274	0.2459	5.367073	2.817059
2459561	RF_maintenance	100.00%	0.00%	0.00%	100.00%	100.00%	0.00%	8.181968	2.649203	1.081195	1.690628	0.618355	0.639545	-1.565920	-1.971745	0.3489	0.3260	-0.2109	4.916019	2.537194
2459560	RF_maintenance	100.00%	0.00%	0.00%	100.00%	100.00%	0.00%	7.427481	2.265004	0.675117	1.503065	0.539697	0.881980	-1.194420	-1.833334	0.3150	0.2911	-0.2122	5.262072	2.448248
2459559	RF_maintenance	100.00%	0.00%	0.00%	100.00%	100.00%	0.00%	7.361394	2.962724	1.309494	2.008197	1.538670	1.243411	-0.875986	-1.567851	0.3416	0.3289	-0.2075	2.902255	2.248930
2459558	RF_maintenance	100.00%	0.00%	0.00%	100.00%	100.00%	0.00%	10.369405	7.432246	12.264505	12.851745	13.932301	16.825406	-0.912283	-1.590795	0.3355	0.3137	-0.2077	2.849199	2.402739
2459557	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0591	0.0677	0.0313	nan	nan
2459556	RF_maintenance	100.00%	0.00%	0.00%	100.00%	100.00%	0.00%	5.728993	8.027124	13.501602	13.380231	17.937870	15.468990	-2.992922	-2.221493	0.3112	0.3232	-0.2574	2.423022	2.555839
2459554	RF_maintenance	-	0.00%	0.00%	100.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.2840	0.2934	-0.2811	nan	nan
2459553	RF_maintenance	-	0.00%	0.00%	100.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.2990	0.3057	-0.2792	nan	nan
2459552	RF_maintenance	100.00%	0.00%	0.00%	100.00%	100.00%	0.00%	13.081431	8.917128	16.483771	18.439033	22.419647	23.294811	1.350967	0.094557	0.3467	0.3291	-0.2077	0.000000	0.000000
2459551	RF_maintenance	100.00%	0.00%	0.00%	100.00%	100.00%	0.00%	8.061740	2.466171	0.997594	1.846219	0.957110	1.205685	-1.425636	-2.057119	0.3484	0.3255	-0.1946	4.720169	2.342408
2459550	RF_maintenance	-	97.53%	97.53%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0569	0.0525	0.0125	nan	nan
2459549	RF_maintenance	100.00%	0.00%	0.00%	100.00%	100.00%	0.00%	12.519705	7.289491	11.776825	13.514391	15.551858	16.225565	-1.944110	-2.384700	0.3457	0.3214	-0.2033	3.485587	2.748578
2459542	RF_maintenance	100.00%	0.00%	0.00%	100.00%	100.00%	0.00%	9.369984	7.280111	25.256537	26.663871	1.297067	1.506166	-0.643516	-1.649507	0.4193	0.4065	-0.2074	2.380212	2.214975
2459541	RF_maintenance	100.00%	1.34%	1.79%	97.76%	100.00%	0.00%	5.959409	6.300404	16.581626	15.844731	10.281307	13.008166	4.332282	4.417913	0.4144	0.4183	-0.2273	2.298003	2.416803
2459540	RF_maintenance	100.00%	0.00%	0.00%	97.32%	100.00%	0.00%	11.384110	3.280018	2.511061	2.841216	1.954157	2.814980	-0.312226	-0.460856	0.4294	0.4153	-0.1769	3.760686	2.325150
2459536	RF_maintenance	100.00%	37.06%	37.06%	62.94%	100.00%	0.00%	16.847349	11.585796	19.880332	22.060442	21.351556	22.762257	-1.754820	-3.162927	0.2548	0.2437	-0.1324	4.478654	2.029218
2459535	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	8.031593	2.497978	2.024662	2.374089	0.471694	5.305269	-0.941984	1.058817	0.0836	0.0776	-0.0047	1.201170	1.202954
2459534	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	8.432375	2.032361	1.113830	1.502876	0.888256	2.091568	-0.193606	-0.982992	0.1019	0.0984	-0.0045	1.164993	1.164975
2459533	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	14.091563	7.589901	12.449019	13.248219	13.181284	14.611811	-1.824738	-2.139875	0.0901	0.0955	-0.0056	1.205107	1.205591
2459532	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	16.927081	8.911554	16.180482	17.039104	16.668785	18.440557	-0.096398	-1.971792	0.0907	0.0903	-0.0074	1.077371	1.074841
2459530	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	7.834312	2.289326	0.942208	1.312633	1.127107	1.356848	0.601466	-0.649128	0.1034	0.0995	-0.0082	1.156142	1.157590
2459527	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	RF_maintenance	100.00%	0.00%	0.00%	100.00%	100.00%	0.00%	17.115511	8.315736	12.857829	13.855691	29.805433	22.098357	-0.683611	-1.369694	0.6958	0.6648	-0.1942	0.000000	0.000000
2459523	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	19.966430	9.567161	17.871285	20.126740	9.198219	25.274118	-5.307838	-5.239825	nan	nan	nan	7.694418	4.801036
2459522	RF_maintenance	100.00%	0.00%	0.00%	100.00%	100.00%	0.00%	10.429611	6.813571	16.633896	16.795160	5.071322	20.188847	-1.890287	-2.240943	0.4238	0.4124	-0.1966	3.090718	2.932689
2459513	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	5.465445	5.250571	10.151987	9.125050	-1.383562	4.443389	-0.177602	-0.664122	0.0455	0.0400	0.0073	nan	nan
2459508	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	15.558453	8.565822	10.398726	10.803280	13.099817	9.644275	10.062501	13.089030	0.1048	0.1018	-0.0036	0.000000	0.000000
2459505	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	82.521615	90.105604	112.028293	107.901186	112.123160	103.759753	781.549815	566.511769	0.0067	0.0068	0.0043	1.059834	1.063692

Antenna Season Report Notebook¶

Antenna 71 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 71, Node 4:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 71: 2459646

Antenna 71: 2459645

Antenna 71: 2459642

Antenna 71: 2459640

Antenna 71: 2459639

Antenna 71: 2459638

Antenna 71: 2459637

Antenna 71: 2459636

Antenna 71: 2459635

Antenna 71: 2459634

Antenna 71: 2459633

Antenna 71: 2459632

Antenna 71: 2459631

Antenna 71: 2459630

Antenna 71: 2459629

Antenna 71: 2459628

Antenna 71: 2459627

Antenna 71: 2459626

Antenna 71: 2459625

Antenna 71: 2459624

Antenna 71: 2459623

Antenna 71: 2459622

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Antenna 71: 2459620

Antenna 71: 2459619

Antenna 71: 2459618

Antenna 71: 2459617

Antenna 71: 2459616

Antenna 71: 2459615

Antenna 71: 2459614

Antenna 71: 2459613

Antenna 71: 2459612

Antenna 71: 2459611

Antenna 71: 2459610

Antenna 71: 2459609

Antenna 71: 2459608

Antenna 71: 2459607

Antenna 71: 2459605

Antenna 71: 2459604

Antenna 71: 2459603

Antenna 71: 2459602

Antenna 71: 2459598

Antenna 71: 2459597

Antenna 71: 2459596

Antenna 71: 2459595

Antenna 71: 2459594

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Antenna 71: 2459589

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Antenna 71: 2459584

Antenna 71: 2459583

Antenna 71: 2459582

Antenna 71: 2459581

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Antenna 71: 2459579

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Antenna 71: 2459577

Antenna 71: 2459576

Antenna 71: 2459575

Antenna 71: 2459574

Antenna 71: 2459573

Antenna 71: 2459572

Antenna 71: 2459571

Antenna 71: 2459570

Antenna 71: 2459569

Antenna 71: 2459566

Antenna 71: 2459565

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶